Borg Debono Victoria, Mbuagbaw Lawrence, Paul James, Buckley Norm, Thabane Lehana
Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main Street West, Health Science Centre-2C, Hamilton, Ontario, L8S 4K1, Canada.
Department of Anesthesia, McMaster University, 1280 Main St. West, Health Science Centre-2V9, Hamilton, Ontario, L8S 4K1, Canada.
Contemp Clin Trials Commun. 2017 May 19;7:81-85. doi: 10.1016/j.conctc.2017.05.005. eCollection 2017 Sep.
Sharing masked interim results by the Data Safety Monitoring Board (DSMB) with non-DSMB members is an important issue that can affect trial integrity. Our survey's objective is to collect evidence to understand how seemingly masked interim results or result extrapolations are interpreted and discuss whether these results should be shared at interim.
Conducted a 6 scenario-question survey asking trial experts how they interpreted three kinds of seemingly masked interim results or result extrapolation measures (interim combined event rate, adaptive conditional power and "unconditional" conditional power).
Thirty-one current Consolidated Standards of Reporting Trials group affiliates were invited for survey participation (February 2015). Response rate: 71.0% (22/31). About half, 52.6% (95% CI: 28.9%-74.0%), (10/19), correctly indicated that the interim combined event rate can be interpreted in three ways (drug X doing better than placebo, worse than placebo or the same) if shared at interim. The majority, 72.2% (95% CI: 46.5%-89.7%), (13/18), correctly indicated that the adaptive conditional power suggests relative treatment group effects. The majority, 53.3% (95% CI: 26.6%-77.0%), (8/15), incorrectly indicated that the "unconditional" conditional power suggests relative treatment group effects.
DISCUSSION/CONCLUSION: Knowledge of these three results or result extrapolation measures should not be shared outside of the DSMB at interim as they may mislead or unmask interim results, potentially introducing trial bias. For example, the interim combined event rate can be interpreted in one of three ways potentially leading to mistaken guesswork about interim results. Knowledge of the adaptive conditional power by non-DSMB members is telling of relative treatment effects thus unmasking of interim results.
数据安全监测委员会（DSMB）与非DSMB成员分享屏蔽的中期结果是一个可能影响试验完整性的重要问题。我们调查的目的是收集证据，以了解看似屏蔽的中期结果或结果推断是如何被解读的，并讨论这些结果在中期是否应该被分享。
开展了一项包含6个情景问题的调查，询问试验专家如何解读三种看似屏蔽的中期结果或结果推断指标（中期合并事件发生率、适应性条件把握度和“无条件”条件把握度）。
邀请了31位当前《报告试验的统一标准》（CONSORT）小组附属成员参与调查（2015年2月）。回复率为71.0%（22/31）。约一半，即52.6%（95%置信区间：28.9%-74.0%），（10/19），正确指出如果在中期分享，中期合并事件发生率可以有三种解读方式（药物X比安慰剂效果好、比安慰剂效果差或相同）。大多数，即72.2%（95%置信区间：46.5%-89.7%），（13/18），正确指出适应性条件把握度表明了相对治疗组效应。大多数，即53.3%（95%置信区间：26.6%-77.0%），（8/15），错误地指出“无条件”条件把握度表明了相对治疗组效应。
讨论/结论：这三种结果或结果推断指标的信息在中期不应在DSMB之外分享，因为它们可能会误导或揭示中期结果，潜在地引入试验偏倚。例如，中期合并事件发生率可以有三种解读方式之一，这可能导致对中期结果的错误猜测。非DSMB成员了解适应性条件把握度会揭示相对治疗效应，从而暴露中期结果。
